I am interested in the combined effects of 12 continuous/interval predictors on a dichotomous/binomial outcome and thus am using logistic regression.
First I ran 12 separate bivariate logistic regressions. All had positive B's. Then when I ran the multiple logistic regression (enter method), some of these predictors have now become negatively associated with the outcome.
I'm not sure what to make of this result. Is this unusual? What does this mean when this happens?
Thanks so much for any guidance!
Bonnie
Best Answer
Welcome to the site.
To keep it simple, let's go to a case with two IVs (the principle is the same). If the $\beta$s are positive in the bivariate regressions it means that as IV 1 increases the odds of "success" (however that is coded) on the DV go up. Similarly for IV 2. If one of the signs (say, that on IV2) switches when including both IVs, it means that the odds of success go down as IV 2 increases, after controlling for IV 1. That is, at constant levels of IV 1, increasing IV 2 lowers the odds of success.
If you tell us what the IVs and the DV are, we will be able to answer more precisely.